{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "data_xls = pd.read_excel(\"2018地区客运量.xlsx\", 'sheet1',index_col = None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls.to_csv('2018地区客运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"国家主要干线客运量.xls\", '年度数据',index_col = None)\n",
    "data_xls.to_csv('国家主要干线客运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"国家主要干线货运量.xls\", '年度数据',index_col = None)\n",
    "data_xls.to_csv('国家主要干线货运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"年客运量.xls\", '年度数据',index_col = None)\n",
    "data_xls.to_csv('年客运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"年货运量.xls\", '年度数据',index_col = None)\n",
    "data_xls.to_csv('年货运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"月客运量.xls\", '月度数据',index_col = None)\n",
    "data_xls.to_csv('月客运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"月客运量.xlsx\", 'Sheet1',index_col = None)\n",
    "data_xls.to_csv('月客运量2.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"月货运量.xls\", '月度数据',index_col = None)\n",
    "data_xls.to_csv('月货运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"月货运量.xlsx\", 'Sheet1',index_col = None)\n",
    "data_xls.to_csv('月货运量2.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"近五年客运量.xlsx\", 'Sheet1',index_col = None)\n",
    "data_xls.to_csv('近五年客运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_xls = pd.read_excel(\"近五年货运量.xlsx\", 'Sheet1',index_col = None)\n",
    "data_xls.to_csv('近五年货运量.csv',encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
